Approximate Optimization Methods and Metaheuristics in Operational Research

ISBN: 9781848212077

Publication Date: September 2010   Hardback   416 pp.

145 USD

eBooks

Description

In the last few decades, a number of powerful methods have been proposed to find satisfactory solutions to management problems of great importance in economies open to competition. They have been successfully applied to solve a large variety of operational problems both in the private and public sector: for example, production scheduling and sequencing, transportation, traffic management, distribution of goods and portfolio selection.
The first half of this book presents an overview of these methods, while the second half focuses on applications. More precisely, it describes how to tailor heuristics to get the best results in a variety of selected typical problems.

Contents

1. Metaheuristics for combinatorial optimization.
2. Implementation principles for metaheuristics.
3. Variable neighborhood search.
4. Noising methods.
5. The ant colony paradigm in combinatorial optimization.
6. GRASP: a greedy randomized heuristic.
7. Using neural nets for combinatorial optimization.
8. Integrating operations research techniques with constraint programming.
9. Application of metaheuristics for coloring the vertices of a graph.
10. Metaheuristics for the vehicle routing problem.
11. Metaheuristics for quadratic assignment.
12. Implementing metaheuristics: case studies.
13. Parallel implementations of metaheuristics.
14. Genetic algorithms applied to production scheduling.
15. Adapting metaheuristics to multicriteria optimization.
16. Flexible constraints satisfaction: application to planning and scheduling problems.